Neural Network-Based Cryptography: A Primary Study on the Performances and Techniques

DOI

10.2991/978-94-6463-094-7_6How to use a DOI?

Keywords

Neural Network; Cryptograph; Generative Adversarial Networks

Abstract

Cybersecurity is getting more and more important in this big data era. Neural Network-based cryptosystem which is a complex system and deserve more research study for improvement. This article will discuss and analyse existing neural network-based cryptography performance and techniques. The in-depth analysis will examine the effectiveness of older structure as well as the effects initiated against them. Several advanced techniques will be discussed that reliant on generative adversarial networks (GANs) to contend with one another in pursuit of a common goal such as efficient encryption for communication. At the end of the paper, it will review a few decent neural network methods best applied on cryptography.

Copyright

© 2022 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jia-Lin Foo
AU  - Kok-Why Ng
AU  - Palanichamy Naveen
PY  - 2022
DA  - 2022/12/27
TI  - Neural Network-Based Cryptography: A Primary Study on the Performances and Techniques
BT  - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
PB  - Atlantis Press
SP  - 68
EP  - 78
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-094-7_6
DO  - 10.2991/978-94-6463-094-7_6
ID  - Foo2022
ER  -